Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction · HackerPapers discussions

Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by a2x

Wed, 19 Aug 2026 18:48:14 GMT

Computational Life Reactor (CLR) is an interactive browser implementation by Alex Borger of the computational-life experiments studied by Agüera y Arcas and collaborators https://arxiv.org/abs/2406.19108. Random byte tapes are repeatedly paired and executed in the BFF language, allowing self-replicating programs to emerge without a fitness function or explicit selection process. CLR provides live population visualizations, frequency and compression measurements, and a step-by-step execution sampler. The simulation runs locally using WebAssembly and parallel browser workers. A great 12 minutes…

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by lioeters

Mon, 03 Aug 2026 08:57:54 GMT

There have been experiments in "digital primordial soup", where primitive programs are cultivated under conditions with evolutionary pressure. Computational Substrates: How Well-formed, Self-replicating Programs Emerge from Simple Interaction - https://arxiv.org/abs/2406.19108 Brainfuck, Forth, Subleq, and most recently Z80 assembly programs with mutations, interactions, and self-modification. Z80 has an LDIR instruction that copies a block of data from one location in memory to another, which allows the "organisms" to reach/discover reproduction quicker and more reliably in repeated…

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by bob1029

Sun, 19 Jul 2026 07:32:21 GMT

See also: https://arxiv.org/abs/2406.19108 > We show that when random, non self-replicating programs are placed in an environment lacking any explicit fitness landscape, self-replicators tend to arise. We demonstrate how this occurs due to random interactions and self-modification, and can happen with and without background random mutations. We also show how increasingly complex dynamics continue to emerge following the rise of self-replicators.

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by markisus

Sat, 18 Jul 2026 23:34:29 GMT

This is every cool research. Do you have any idea why the authors chose Z80 as the program language? I have seen other studies in the same spirit that use simpler toy languages like Brainfuck (https://arxiv.org/abs/2406.19108) and I wonder if you could get higher execution speed if you didn't have to execute so much emulator code. The programs/genomes are extremely tiny. I would be very interested to see what kind of hardware is needed to scale this approach up. How long until we can feed in giant corpuses of text and evolve these little organisms to predict the next letter?

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by bob1029

Sun, 16 Nov 2025 14:24:02 GMT

This paper? https://arxiv.org/abs/2406.19108 I've read it many times. It introduced me to the idea of using self-modifying programs. I've built several prototypes that use their exact instruction set, but I haven't found a way to guide the evolution in a desired direction yet. The self-modifying aspect can be quite destructive to the genome.

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by bob1029

Sat, 01 Nov 2025 15:29:23 GMT

> The advent of large language models have made this type of content relatively easy to churn out on demand, and the majority of the review articles we receive are little more than annotated bibliographies, with no substantial discussion of open research issues. I have to agree with their justification. Since "Attention Is All You Need" (2017) I have seen maybe four papers with similar impact in the AI/ML space. The signal to noise ratio is really awful. If I had to pick a semi-related paper published since 2020 that I actually found interesting, it would have to be this one…

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by bob1029

Thu, 12 Dec 2024 03:38:17 GMT

https://arxiv.org/abs/2406.19108

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by bob1029

Thu, 14 Nov 2024 21:57:13 GMT

This sounds like something more up the alley of linear genetic programming. There are some very interesting experiments out there that utilize UTMs (BrainFuck, Forth, et. al.) [0,1,2]. I've personally had some mild success getting these UTM variants to output their own children in a meta programming arrangement. The base program only has access to the valid instruction set of ~12 instructions per byte, while the task program has access to the full range of instructions and data per byte (256). By only training the base program, we reduce the search space by a very substantial factor. I think…

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by bob1029

Mon, 23 Sep 2024 17:05:05 GMT

Brainfuck is largely a joke for most developers, but in certain kinds of research it is taken very seriously due to its ease of implementation. I think this is probably the most interesting paper involving it: https://arxiv.org/abs/2406.19108 > In this paper we take a step towards understanding how self-replicators arise by studying several computational substrates based on various simple programming languages and machine instruction sets.

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by smusamashah

Fri, 23 Aug 2024 11:36:57 GMT

It's an implementation of Google's research https://arxiv.org/abs/2406.19108 Previous discussions: https://news.ycombinator.com/item?id=40820022 https://news.ycombinator.com/item?id=41080435 Since author hasn't setup a github.io link, you can try it using githack https://rawcdn.githack.com/znah/zff/3e58d9742681bc3358059052...

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by netcraft

Fri, 26 Jul 2024 17:59:41 GMT

previously: https://news.ycombinator.com/item?id=40820022 Link directly to the arxiv paper: https://arxiv.org/abs/2406.19108

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by raidicy

Fri, 26 Jul 2024 17:59:08 GMT

https://arxiv.org/abs/2406.19108 Here's a direct link to the paper. I have not read it yet but the abstract reminds me of a recent post discussing using brainfuck as a way to do program synthesis.

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — mentioned by Out_of_Characte

Mon, 22 Jul 2024 14:51:58 GMT

Synthetic and generated data might not be garbage. Consider random chess positions. Those are generated,yet there's an engine out there that has objectively a higher chance of winning from that position. There was also a paper on persistent computer programs after running random data iteratively over millions of cycles. This doesn't even have a 'goal'. which by itself is very interesting because of how similar it feels to how organisms develop by the act of persisting after a few billion years. That is to say I largely agree with the premise that you can train and improve alot by absense of…

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Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — HN submission

Sun, 30 Jun 2024 15:22:07 GMT

Computational Life: How Self-Replicating Programs Emerge from Simple Interaction

4 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction — HN submission

Fri, 28 Jun 2024 12:36:00 GMT

Computational Life: How self-replicating programs emerge from simple interaction

141 points; 17 discussion replies on HN. Paper and source history. A submission is not an endorsement.